中国商业银行收入结构与经营效率分析

发布时间：2018-05-04 07:54

本文选题：技术效率 + 纯技术效率　；参考：《山东财经大学》2013年硕士论文

【摘要】：目前，中国商业银行以传统的存贷款业务为主，利息收入占收入来源的绝大多数。而国外商业银行在传统存贷款业务的基础上，大力发展非利息收入业务，非利息收入占比达到40%以上。随着金融全球化，中国金融体制改革的不断推进及银行业的全面对外开放，中国商业银行传统的存贷款业务受到严重冲击，越来越多的商业银行开始重视发展非利息收入业务。首先，本文运用描述性统计方法，对目前国内外商业银行收入结构进行分析，并用定性分析法研究了二者之间存在差异的原因。其次，利用前沿效率分析法中的超效率DEA模型，对中国商业银行的经营效率（包括技术效率、纯技术效率和规模效率）进行测算。并在此基础上利用面板数据模型，建立回归方程，测算利息收入，非利息收入、非利息收入的不同组成部分及其他控制变量对商业银行经营效率的影响。最后，，根据实证结果，提出促进商业银行改善收入结构，提高经营效率的政策建议。通过实证分析，得出：第一，利息收入与商业银行经营效率正相关，非利息收入与商业银行经营效率负相关，其中非利息收入对技术效率和纯技术效率的负面影响较为显著。第二，资产占比与商业银行的技术效率和规模效率负相关，与纯技术效率正相关。第三，资本增长率对商业银行经营效率没有显著性影响。第四，资产费用率与商业银行的技术效率和纯技术效率负相关，与规模效率具有不显著的正相关。第五，存贷比对商业银行技术效率的影响不显著，但与纯技术效率正相关，与规模效率负相关。第六，从整体来看，手续费及佣金收入可以促进商业银行提高经营效率。投资收入和其他收入与商业银行经营效率负相关。本文的创新点主要表现在以下两个方面：第一，使用技术效率、纯技术效率及规模效率作为衡量商业银行经营效率的标准，并在此基础上研究商业银行收入结构与经营效率的关系。第二，运用三种效率的超效率DEA值作为被解释变量，商业银行非利息收入的不同组成部分作为解释变量，建立面板数据模型进行归回分析。
[Abstract]:At present, the traditional deposit and loan business is the main business of Chinese commercial banks, and interest income accounts for the vast majority of income sources. On the basis of traditional deposit and loan business, foreign commercial banks vigorously develop non-interest income business, which accounts for more than 40% of non-interest income. With the financial globalization, the continuous promotion of China's financial system reform and the overall opening up of the banking sector, the traditional deposit and loan business of Chinese commercial banks has been seriously affected, and more and more commercial banks have begun to attach importance to the development of non-interest income business. First of all, this paper uses descriptive statistical method to analyze the income structure of commercial banks at home and abroad, and uses qualitative analysis method to study the reasons for the difference between the two. Secondly, the operational efficiency of Chinese commercial banks (including technical efficiency, pure technical efficiency and scale efficiency) is measured by using the super-efficiency DEA model of frontier efficiency analysis. On the basis of this, the regression equation is established by using panel data model, and the effects of different components of interest income, non-interest income, non-interest income and other control variables on the operating efficiency of commercial banks are calculated. Finally, according to the empirical results, the paper puts forward some policy suggestions to promote commercial banks to improve their income structure and management efficiency. Through empirical analysis, it is concluded that: first, interest income is positively related to commercial bank operating efficiency, and non-interest income is negatively related to commercial bank operating efficiency, in which non-interest income has a significant negative impact on technical efficiency and pure technical efficiency. Second, the proportion of assets is negatively correlated with the technical efficiency and scale efficiency of commercial banks, and is positively correlated with pure technical efficiency. Third, the growth rate of capital has no significant effect on the operating efficiency of commercial banks. Fourthly, the asset expense rate is negatively correlated with the technical efficiency and pure technical efficiency of commercial banks, but has no significant positive correlation with the scale efficiency. Fifth, the ratio of deposit to loan has no significant effect on the technical efficiency of commercial banks, but it is positively related to pure technical efficiency and negatively related to scale efficiency. Sixth, from the overall point of view, fees and commissions can promote the efficiency of commercial banks. Investment income and other income are negatively correlated with commercial bank operating efficiency. The innovations of this paper are as follows: first, using technical efficiency, pure technical efficiency and scale efficiency as the standard to measure the operational efficiency of commercial banks. On this basis, the relationship between income structure and operating efficiency of commercial banks is studied. Secondly, using the DEA value of three kinds of efficiency superefficiency as the explanatory variable and the different components of non-interest income of commercial banks as explanatory variables, the panel data model is established for regression analysis.
【学位授予单位】：山东财经大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：F832.33

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